diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index a15f8a515..87e53cf19 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -67,7 +67,7 @@ class Model: model_arch: gguf.MODEL_ARCH def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool, metadata: gguf.Metadata, - model_name: str | None, split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, small_first_shard: bool = False): + split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, small_first_shard: bool = False): if type(self) is Model: raise TypeError(f"{type(self).__name__!r} should not be directly instantiated") @@ -107,21 +107,6 @@ class Model: self.gguf_writer = gguf.GGUFWriter(path=None, arch=gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file, split_max_tensors=split_max_tensors, split_max_size=split_max_size, dry_run=dry_run, small_first_shard=small_first_shard) - # Update any missing authorship metadata with HuggingFace parameters or model card frontmatter - if self.metadata is not None: - - # Source Hugging Face Repository - if self.metadata.source_hf_repo is None: - if self.hparams is not None and "_name_or_path" in self.hparams: - self.metadata.source_hf_repo = self.hparams["_name_or_path"] - - # Model License - if self.metadata.license is None: - if self.model_card is not None and "license" in self.model_card: - self.metadata.source_hf_repo = self.model_card["license"] - - self.model_name = Model.get_model_name(self.metadata, self.hparams, self.dir_model, self.model_arch) - # Fallback to model architecture name if metadata name is still missing if self.metadata.name is None: self.metadata.name = gguf.MODEL_ARCH_NAMES[self.model_arch] @@ -3708,8 +3693,8 @@ def main() -> None: logger.error(f"Model {hparams['architectures'][0]} is not supported") sys.exit(1) - model_instance = model_class(dir_model, output_type, fname_out, args.bigendian, args.use_temp_file, args.no_lazy, - metadata, args.model_name, split_max_tensors=args.split_max_tensors, + model_instance = model_class(dir_model, output_type, fname_out, args.bigendian, args.use_temp_file, + args.no_lazy, metadata, split_max_tensors=args.split_max_tensors, split_max_size=split_str_to_n_bytes(args.split_max_size), dry_run=args.dry_run, small_first_shard=args.no_tensor_first_split)